| scholarly article | Q13442814 |
| P2093 | author name string | James Hanley | |
| Nancy E Mayo | |||
| Stella S Daskalopoulou | |||
| Lyne Nadeau | |||
| Lisa Nobel | |||
| P2860 | cites work | Primary prevention of ischemic stroke | Q22306369 |
| Assessing influence in regression analysis with censored data | Q31027693 | ||
| The validation of the Finnish Hospital Discharge Register and Causes of Death Register data on stroke diagnoses | Q31115680 | ||
| Validation of ICD-9 codes with a high positive predictive value for incident strokes resulting in hospitalization using Medicaid health data | Q31135274 | ||
| Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology | Q33740111 | ||
| Alcohol consumption and risk of stroke: a meta-analysis | Q34176407 | ||
| Meta-analysis of relation between cigarette smoking and stroke | Q34662740 | ||
| Follow-up report on the diagnosis of diabetes mellitus | Q35567871 | ||
| Measuring accuracy of discharge diagnoses for a region-wide surveillance of hospitalized strokes | Q36080168 | ||
| Coding of stroke and stroke risk factors using international classification of diseases, revisions 9 and 10. | Q36195427 | ||
| Healthy lifestyle and the risk of stroke in women. | Q36532647 | ||
| Reducing the growing burden of cardiovascular disease in the developing world | Q36628358 | ||
| Exercise as stroke prophylaxis | Q37460046 | ||
| A review of goodness of fit statistics for use in the development of logistic regression models | Q40338804 | ||
| Estimates of global and regional potential health gains from reducing multiple major risk factors | Q40571153 | ||
| Clinical prediction rules. A review and suggested modifications of methodological standards | Q41340678 | ||
| Modeling of risk factors for ischemic stroke. The Willis Lecture | Q41597148 | ||
| Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study | Q43012682 | ||
| A prospective study of maturity-onset diabetes mellitus and risk of coronary heart disease and stroke in women | Q44170464 | ||
| Joint effects of risk factors for stroke and transient ischemic attack in a German population: the EPIC Potsdam Study | Q45180948 | ||
| Trends in community knowledge of the warning signs and risk factors for stroke | Q46156146 | ||
| Body size and fat distribution as predictors of stroke among US men. | Q47319773 | ||
| Accuracy of ICD-9 codes in identifying ischemic stroke in the General Hospital of Lugo di Romagna (Italy). | Q47802674 | ||
| Surveillance for stroke in Canada. | Q48224417 | ||
| Anger expression and incident stroke: prospective evidence from the Kuopio ischemic heart disease study | Q48270117 | ||
| Incidence, natural history and cardiovascular events in symptomatic and asymptomatic peripheral arterial disease in the general population. | Q50974758 | ||
| Profile-specific survival estimates: making reports of clinical trials more patient-relevant. | Q51889633 | ||
| Depressive symptoms and risk of stroke: the Rotterdam Study. | Q51894772 | ||
| The Breslow estimator of the nonparametric baseline survivor function in Cox's regression model: some heuristics. | Q51898207 | ||
| Ignoring social factors in clinical decision rules: a contribution to health inequalities? | Q53280334 | ||
| Depressive Symptoms and Risk of Stroke: The Framingham Study | Q54877439 | ||
| Probability of stroke: a risk profile from the Framingham Study | Q57746223 | ||
| Manifestations of coronary disease predisposing to stroke. The Framingham study | Q57746367 | ||
| Accuracy of the ICD-9 codes for identifying TIA and stroke in an Italian automated database | Q59683440 | ||
| Impact of multiple risk factor profiles on determining cardiovascular disease risk | Q64133367 | ||
| Diabetes and the risk of stroke. The Honolulu Heart Program | Q69730010 | ||
| [Theoretical and practical problems in the measurement of the mental health of populations. Quebec health survey] | Q69771394 | ||
| Body fat, coronary heart disease, and stroke in Japanese men | Q70152892 | ||
| Lifestyle factors and chronic diseases: application of a composite risk index | Q73146053 | ||
| The evolution of stroke in Quebec: a 15-year perspective | Q80087801 | ||
| Chronic kidney disease and cardiovascular disease in a general Japanese population: the Hisayama Study | Q81847255 | ||
| P275 | copyright license | Creative Commons Attribution-NonCommercial 3.0 Unported | Q18810331 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 1 | |
| P304 | page(s) | 1-9 | |
| P577 | publication date | 2014-01-06 | |
| P1433 | published in | Journal of clinical neurology | Q26841853 |
| P1476 | title | MyRisk_Stroke Calculator: A Personalized Stroke Risk Assessment Tool for the General Population | |
| P478 | volume | 10 |
| Q30242055 | Anger and stroke: a potential association that deserves serious consideration |
| Q99617634 | Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models |
| Q92756434 | Chinese primary knee osteoarthritis progression cohort (CPKOPC) to evaluate the progression of knee osteoarthritis in the Beijing population: a prospective cohort study protocol |
| Q36201923 | Development and feasibility of a personalized, interactive risk calculator for knee osteoarthritis |
| Q108126970 | Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank |
| Q57482496 | Prevention of stroke: a global perspective |
| Q40511591 | Randomized Controlled Trial of an Educational Intervention Using an Online Risk Calculator for Knee Osteoarthritis: Effect on Risk Perception |
Search more.